get_engagement_stats

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what metrics are computed and the benchmarking purpose, but doesn't mention important behavioral aspects like rate limits, authentication requirements, data freshness (how recent is 'recent'), computational cost, or error conditions. The description doesn't contradict any annotations since none exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in two sentences: the first explains what the tool does and returns, the second explains its purpose. Every word earns its place with no redundancy or unnecessary elaboration. It's appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no annotations and no output schema, the description provides adequate purpose and usage context but leaves gaps in behavioral transparency. For a tool that computes metrics across multiple videos, more information about performance characteristics, data limitations, or result interpretation would be helpful. The description is complete enough for basic understanding but could be more comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, both parameters are well-documented in the schema itself. The description doesn't add any parameter-specific information beyond what's already in the schema descriptions. The baseline score of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('computes per-video engagement metrics'), resource ('across a channel's recent videos'), and output ('average views, likes, comments, like rate %, comment rate %, overall engagement rate %, and the top engaging video'). It distinguishes itself from siblings like get_channel_overview or get_video_details by focusing specifically on engagement metrics rather than general channel info or individual video details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool ('Great for benchmarking your channel's audience engagement health'), which implicitly suggests it's for channel performance analysis rather than individual video analysis. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools for different analytical needs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.